2026-02-19

AIOS Observability: Traces, Metrics, and Evaluations

Primary keyword: AIOS observability

Observability is the difference between hoping agents work and knowing why they work. AIOS observability should include traces, metrics, and evaluation loops tied to real business outcomes.

Trace data should capture model prompts, tool calls, policy checks, and state transitions. This enables practical debugging when behavior drifts or external systems respond unpredictably.

Metrics should include completion rate, cycle time, exception rate, human intervention frequency, and cost per completed task. Without these, optimization decisions are mostly guesswork.

Evaluation harnesses close the loop. Regression tests against known scenarios catch behavior changes before they affect production workflows, especially after prompt, model, or connector updates.

Tags: Observability, Evaluation